Triple
T14253908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arc of Infinity |
E353336
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Johnny Byrne
Johnny Byrne was a British television writer best known for his work on series such as Doctor Who and All Creatures Great and Small.
|
E1105396
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Johnny Byrne | Statement: [Arc of Infinity, writer, Johnny Byrne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johnny Byrne Context triple: [Arc of Infinity, writer, Johnny Byrne]
-
A.
John Ronane
John Ronane was a British actor known for his work in film, television, and theatre, including a role in the drama "Elizabeth R."
-
B.
Jonathan Kerrigan
Jonathan Kerrigan is a British actor known for his roles in television dramas such as Casualty, Heartbeat, and In the Club.
-
C.
Jack Doolan
Jack Doolan is a British actor best known for his role in the coming-of-age comedy-drama film "Cemetery Junction" and various appearances in UK television series.
-
D.
Michael Byrne
Michael Byrne is a British character actor known for his numerous film and television roles, often portraying military officers or authority figures.
-
E.
Roy Coyle
Roy Coyle is a highly successful Northern Irish football manager best known for his trophy-laden spell in charge of Linfield FC.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Johnny Byrne Triple: [Arc of Infinity, writer, Johnny Byrne]
Generated description
Johnny Byrne was a British television writer best known for his work on series such as Doctor Who and All Creatures Great and Small.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Johnny Byrne Target entity description: Johnny Byrne was a British television writer best known for his work on series such as Doctor Who and All Creatures Great and Small.
-
A.
John Ronane
John Ronane was a British actor known for his work in film, television, and theatre, including a role in the drama "Elizabeth R."
-
B.
Jonathan Kerrigan
Jonathan Kerrigan is a British actor known for his roles in television dramas such as Casualty, Heartbeat, and In the Club.
-
C.
Jack Doolan
Jack Doolan is a British actor best known for his role in the coming-of-age comedy-drama film "Cemetery Junction" and various appearances in UK television series.
-
D.
Michael Byrne
Michael Byrne is a British character actor known for his numerous film and television roles, often portraying military officers or authority figures.
-
E.
Roy Coyle
Roy Coyle is a highly successful Northern Irish football manager best known for his trophy-laden spell in charge of Linfield FC.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6297f38c819090d7c7fd8bfa2e9e |
completed | April 14, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a31ef388190bc3082abc1c25ff4 |
completed | May 8, 2026, 5:52 a.m. |
| NEDg | Description generation | batch_69fd7cac286c8190a87bbcd3b7d4d3ac |
completed | May 8, 2026, 6:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd7d24601c8190a95567703123e33b |
completed | May 8, 2026, 6:05 a.m. |
Created at: April 10, 2026, 1:09 a.m.